No evidence of structural abnormality of the substantia nigra in adult attention-deficit/hyperactivity disorder: a pilot cross-sectional cohort study.

Background: Abnormal expansion of the echogenic substantia nigra (SN+) is a common observation in Parkinson's disease (PD) and considered a potential trait marker within this context. However, SN+ was also frequently detected in children diagnosed with attention-deficit/hyperactivity disorder (ADHD), where it has been discussed as a biomarker of maturational dopaminergic dysfunction. Interestingly, ADHD was recently linked to an elevated risk of PD in epidemiological studies, particularly among individuals treated with psychostimulants. Here, we investigated the potential of SN echogenicity as a disease biomarker in adults with ADHD and its relation to psychostimulant treatment. Methods: In an exploratory cross-sectional cohort study, we performed transcranial sonography of the SN in 30 adults (mean age 33.3 ± 7.6 years, 19 males/11 females) diagnosed with ADHD according to DSM-V criteria. Results and conclusions: In this pilot study, we observed no evidence of structural abnormalities of the SN among adults diagnosed with ADHD, thus questioning the potential of SN+ as a biomarker for ADHD in this population. Moreover, we found no evidence of treatment-related SN echogenicity changes that would link therapeutic psychostimulant use to alterations in the structural integrity of the SN.

Regional Anesthesia in the Elite Athlete.

Elite athletes are exposed to an elevated risk of musculoskeletal injury which may present a significant threat to an athlete's livelihood. The perioperative anesthetic plan of care for these injuries in the general population often incorporates regional anesthesia procedures due to several benefits. However, some concern exists regarding the potential for regional anesthesia to adversely impact functional recovery in an elite athlete who may have a lower tolerance for this risk. This article aims to review the data behind this concern, discuss strategies to improve the safety of these procedures and explore the features of consent in this patient population.

Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19.

The emergence of the SARS-CoV-2 virus and new viral variations with higher transmission and mortality rates have highlighted the urgency to accelerate vaccination to mitigate the morbidity and mortality of the COVID-19 pandemic. For this purpose, this paper formulates a new multi-vaccine, multi-depot location-inventory-routing problem for vaccine distribution. The proposed model addresses a wide variety of vaccination concerns: prioritizing age groups, fair distribution, multi-dose injection, dynamic demand, etc. To solve large-size instances of the model, we employ a Benders decomposition algorithm with a number of acceleration techniques. To monitor the dynamic demand of vaccines, we propose a new adjusted susceptible-infectious-recovered (SIR) epidemiological model, where infected individuals are tested and quarantined. The solution to the optimal control problem dynamically allocates the vaccine demand to reach the endemic equilibrium point. Finally, to illustrate the applicability and performance of the proposed model and solution approach, the paper reports extensive numerical experiments on a real case study of the vaccination campaign in France. The computational results show that the proposed Benders decomposition algorithm is 12 times faster, and its solutions are, on average, 16% better in terms of quality than the Gurobi solver under a limited CPU time. In terms of vaccination strategies, our results suggest that delaying the recommended time interval between doses of injection by a factor of 1.5 reduces the unmet demand up to 50%. Furthermore, we observed that the mortality is a convex function of fairness and an appropriate level of fairness should be adapted through the vaccination.

Production-sharing of critical resources with dynamic demand under pandemic situation: The COVID-19 pandemic.

The COVID-19 virus's high transmissibility has resulted in the virus's rapid spread throughout the world, which has brought several repercussions, ranging from a lack of sanitary and medical products to the collapse of medical systems. Hence, governments attempt to re-plan the production of medical products and reallocate limited health resources to combat the pandemic. This paper addresses a multi-period production-inventory-sharing problem (PISP) to overcome such a circumstance, considering two consumable and reusable products. We introduce a new formulation to decide on production, inventory, delivery, and sharing quantities. The sharing will depend on net supply balance, allowable demand overload, unmet demand, and the reuse cycle of reusable products. Undeniably, the dynamic demand for products during pandemic situations must be reflected effectively in addressing the multi-period PISP. A bespoke compartmental susceptible-exposed-infectious-hospitalized-recovered-susceptible (SEIHRS) epidemiological model with a control policy is proposed, which also accounts for the influence of people's behavioral response as a result of the knowledge of adequate precautions. An accelerated Benders decomposition-based algorithm with tailored valid inequalities is offered to solve the model. Finally, we consider a realistic case study - the COVID-19 pandemic in France - to examine the computational proficiency of the decomposition method. The computational results reveal that the proposed decomposition method coupled with effective valid inequalities can solve large-sized test problems in a reasonable computational time and 9.88 times faster than the commercial Gurobi solver. Moreover, the sharing mechanism reduces the total cost of the system and the unmet demand on the average up to 32.98% and 20.96%, respectively.

Laparoscopic Repair of a Right-Sided Diaphragmatic Hernia: A Technical Report.

Introduction: Occult diaphragmatic hernias after trauma are relatively rare and may present months to years after the traumatic event. Clinical presentations range from asymptomatic incidental findings on imaging to life-threatening incarceration of abdominal visceral organs. This study presents a case of a patient with a symptomatic diaphragmatic hernia secondary to a trauma >30 years prior. A literature review of this defect was performed examining the pathophysiology, presentation, and operative considerations. Case Presentation: A 58-year-old male with a history of multiple traumatic motor vehicle accidents 30 years prior presented with abdominal pain and obstructive symptoms. Axial imaging demonstrated a right-sided diaphragmatic hernia defect containing small intestine, colon, and omentum. He ultimately underwent a transabdominal laparoscopic repair of the defect with mesh buttressing. Postoperative the patient recovered well and was discharged without complications. Conclusion: Limited data outside of case reports exist for surgical management of occult diaphragmatic hernias secondary to trauma. Reported management options include open and minimally invasive thoracic as well as open and minimally invasive abdominal approaches; each with advantages and disadvantages. Depending on the defect size, both primary repair and repair with mesh reinforcement are appropriate options. More data comparing the approach and repair technique are needed to determine the best technique.

Low-Cost Sensor Node for Air Quality Monitoring: Field Tests and Validation of Particulate Matter Measurements.

Air pollution is still a major public health issue, which makes monitoring air quality a necessity. Mobile, low-cost air quality measurement devices can potentially deliver more coherent data for a region or municipality than stationary measurement stations are capable of due to their improved spatial coverage. In this study, air quality measurements obtained during field tests of our low-cost air quality sensor node (sensor-box) are presented and compared to measurements from the regional air quality monitoring network. The sensor-box can acquire geo-tagged measurements of several important pollutants, as well as other environmental quantities such as light and sound. The field test consists of sensor-boxes mounted on utility vehicles operated by municipalities located in Central Switzerland. Validation is performed against a measurement station that is part of the air quality monitoring network of Central Switzerland. Often not discussed in similar studies, this study tests and discusses several data filtering methods for the removal of outliers and unfeasible values prior to further analysis. The results show a coherent measurement pattern during the field tests and good agreement to the reference station during the side-by-side validation test.

Automated Open-Hardware Multiwell Imaging Station for Microorganisms Observation.

Bright field microscopes are particularly useful tools for biologists for cell and tissue observation, phenotyping, cell counting, and so on. Direct cell observation provides a wealth of information on cells' nature and physiological condition. Microscopic analyses are, however, time-consuming and usually not easy to parallelize. We describe the fabrication of a stand-alone microscope able to automatically collect samples with 3D printed pumps, and capture images at up to 50× optical magnification with a digital camera at a good throughput (up to 24 different samples can be collected and scanned in less than 10 min). Furthermore, the proposed device can store and analyze pictures using computer vision algorithms running on a low power integrated single board computer. Our device can perform a large set of tasks, with minimal human intervention, that no single commercially available machine can perform. The proposed open-hardware device has a modular design and can be freely reproduced at a very competitive price with the use of widely documented and user-friendly components such as Arduino, Raspberry pi, and 3D printers.

Validating GAN-BioBERT: A Methodology for Assessing Reporting Trends in Clinical Trials.

Background: The aim of this study was to validate a three-class sentiment classification model for clinical trial abstracts combining adversarial learning and the BioBERT language processing model as a tool to assess trends in biomedical literature in a clearly reproducible manner. We then assessed the model's performance for this application and compared it to previous models used for this task. Methods: Using 108 expert-annotated clinical trial abstracts and 2,000 unlabeled abstracts this study develops a three-class sentiment classification algorithm for clinical trial abstracts. The model uses a semi-supervised model based on the Bidirectional Encoder Representation from Transformers (BERT) model, a much more advanced and accurate method compared to previously used models based upon traditional machine learning methods. The prediction performance was compared to those previous studies. Results: The algorithm was found to have a classification accuracy of 91.3%, with a macro F1-Score of 0.92, significantly outperforming previous studies used to classify sentiment in clinical trial literature, while also making the sentiment classification finer grained with greater reproducibility. Conclusion: We demonstrate an easily applied sentiment classification model for clinical trial abstracts that significantly outperforms previous models with greater reproducibility and applicability to large-scale study of reporting trends.

Distinction of Lymphoma from Sarcoidosis on 18F-FDG PET/CT: Evaluation of Radiomics-Feature-Guided Machine Learning Versus Human Reader Performance.

Sarcoidosis and lymphoma often share common features on 18F-FDG PET/CT, such as intense hypermetabolic lesions in lymph nodes and multiple organs. We aimed at developing and validating radiomics signatures to differentiate sarcoidosis from Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma (DLBCL). Methods: We retrospectively collected 420 patients (169 sarcoidosis, 140 HL, and 111 DLBCL) who underwent pretreatment 18F-FDG PET/CT at the University Hospital of Liege. The studies were randomly distributed to 4 physicians, who gave their diagnostic suggestion among the 3 diseases. The individual and pooled performance of the physicians was then calculated. Interobserver variability was evaluated using a sample of 34 studies interpreted by all physicians. Volumes of interest were delineated over the lesions and the liver using MIM software, and 215 radiomics features were extracted using the RadiomiX Toolbox. Models were developed combining clinical data (age, sex, and weight) and radiomics (original and tumor-to-liver TLR radiomics), with 7 different feature selection approaches and 4 different machine-learning (ML) classifiers, to differentiate sarcoidosis and lymphomas on both lesion-based and patient-based approaches. Results: For identifying lymphoma versus sarcoidosis, physicians' pooled sensitivity, specificity, area under the receiver-operating-characteristic curve (AUC), and accuracy were 0.99 (95% CI, 0.97-1.00), 0.75 (95% CI, 0.68-0.81), 0.87 (95% CI, 0.84-0.90), and 89.3%, respectively, whereas for identifying HL in the tumor population, it was 0.58 (95% CI, 0.49-0.66), 0.82 (95% CI, 0.74-0.89), 0.70 (95% CI, 0.64-0.75) and 68.5%, respectively. Moderate agreement was found among observers for the diagnosis of lymphoma versus sarcoidosis and HL versus DLBCL, with Fleiss κ-values of 0.66 (95% CI, 0.45-0.87) and 0.69 (95% CI, 0.45-0.93), respectively. The best ML models for identifying lymphoma versus sarcoidosis showed an AUC of 0.94 (95% CI, 0.93-0.95) and 0.85 (95% CI, 0.82-0.88) in lesion- and patient-based approaches, respectively, using TLR radiomics (plus age for the second). To differentiate HL from DLBCL, we obtained an AUC of 0.95 (95% CI, 0.93-0.96) in the lesion-based approach using TLR radiomics and 0.86 (95% CI, 0.80-0.91) in the patient-based approach using original radiomics and age. Conclusion: Characterization of sarcoidosis and lymphoma lesions is feasible using ML and radiomics, with very good to excellent performance, equivalent to or better than that of physicians, who showed significant interobserver variability in their assessment.

Regional Anesthesia in the Elite Athlete.

Elite athletes are exposed to an elevated risk of musculoskeletal injury which may present a significant threat to an athlete's livelihood. The perioperative anesthetic plan of care for these injuries in the general population often incorporates regional anesthesia procedures due to several benefits. However, some concern exists regarding the potential for regional anesthesia to adversely impact functional recovery in an elite athlete who may have a lower tolerance for this risk. This article aims to review the data behind this concern, discuss strategies to improve the safety of these procedures and explore the features of consent in this patient population.

Integrating Clinical Reasoning Skills in a Pre-professional Undergraduate Human Anatomy Course.

Clinically integrated curricula in health science education has been shown to promote the development of problem-solving schema and positively impact knowledge acquisition. Despite its' purported benefits, this type of curricula can impose a high cognitive load, which may negatively impact novice learners' knowledge acquisition and problem-solving schema development. Introducing explicit clinical reasoning instruction within pre-professional undergraduate basic science courses may limit factors that increase cognitive load, enhance knowledge acquisition, and foster developing clinical problem-solving skills. This study, conducted over the Fall and Spring semesters of the 2018-2019 school year, sought to evaluate whether the implementation of a clinical reasoning instructional intervention within a clinically integrated pre-professional undergraduate general human anatomy course influenced students' acquisition of anatomical knowledge and development of clinical problem-solving skills. Results of the study were mixed regarding the acquisition of anatomical knowledge. Both the intervention and comparison groups performed similarly on multiple choice examinations of anatomical knowledge. However, the clinical reasoning intervention positively impacted students' ability to apply clinical reasoning skills to anatomically based clinical case studies. Results from M\mixed between-within subjects analysis of variance comparing scores on Written Clinical Reasoning Assessments revealed a significant interaction between time and group affiliation, with the groups receiving the interventions outperforming the comparison groups: Fall, P < 0.001; Spring, P < 0.001. The results of this study may imply that explicit clinical reasoning instruction within a clinically integrated undergraduate Human Anatomy course could hold potential for fostering students' early clinical reasoning skills.

Thermoplastic Composites for Integrally Woven Pressure Actuated Cellular Structures: Design Approach and Material Investigation.

The use of pressure-actuated cellular structures (PACS) is an effective approach for the application of compliant mechanisms. Analogous to the model in nature, the Venus flytrap, they are made of discrete pressure-activated rows and can be deformed with high stiffness at a high deformation rate. In previous work, a new innovative approach in their integral textile-based manufacturing has been demonstrated based on the weaving technique. In this work, the theoretical and experimental work on the further development of PACS from simple single-row to double-row PACS with antagonistic deformation capability is presented. Supported by experimental investigations, the necessary adaptations in the design of the textile preform and the polymer composite design are presented and concretized. Based on the results of pre-simulations of the deformation capacity of the new PACS, their performance was evaluated, the results of which are presented.

[18F]FDG PET radiomics to predict disease-free survival in cervical cancer: a multi-scanner/center study with external validation.

PURPOSE: To test the performances of native and tumour to liver ratio (TLR) radiomic features extracted from pre-treatment 2-[18F] fluoro-2-deoxy-D-glucose ([18F]FDG) PET/CT and combined with machine learning (ML) for predicting cancer recurrence in patients with locally advanced cervical cancer (LACC). METHODS: One hundred fifty-eight patients with LACC from multiple centers were retrospectively included in the study. Tumours were segmented using the Fuzzy Local Adaptive Bayesian (FLAB) algorithm. Radiomic features were extracted from the tumours and from regions drawn over the normal liver. Cox proportional hazard model was used to test statistical significance of clinical and radiomic features. Fivefold cross validation was used to tune the number of features. Seven different feature selection methods and four classifiers were tested. The models with the selected features were trained using bootstrapping and tested in data from each scanner independently. Reproducibility of radiomics features, clinical data added value and effect of ComBat-based harmonisation were evaluated across scanners. RESULTS: After a median follow-up of 23 months, 29% of the patients recurred. No individual radiomic or clinical features were significantly associated with cancer recurrence. The best model was obtained using 10 TLR features combined with clinical information. The area under the curve (AUC), F1-score, precision and recall were respectively 0.78 (0.67-0.88), 0.49 (0.25-0.67), 0.42 (0.25-0.60) and 0.63 (0.20-0.80). ComBat did not improve the predictive performance of the best models. Both the TLR and the native models performance varied across scanners used in the test set. CONCLUSION: [18F]FDG PET radiomic features combined with ML add relevant information to the standard clinical parameters in terms of LACC patient's outcome but remain subject to variability across PET/CT devices.

Open-hardware wireless controller and 3D-printed pumps for efficient liquid manipulation.

Many routines in biological experiments require the precise handling of liquid volumes in the range of microliters up to liters. In this paper, we describe a new wireless controller that is adapted to liquid manipulation tasks, in particular when combined with the proposed 3D-printed pumps. It can be built from widely available electronic components and managed with open-source software. The use of peristaltic pumps enables to move volumes from milliliters to liters with a relative error below 1% or a syringe pump capable of injecting volumes in the range of milliliters with microliter accuracy. The system is remotely controllable over WiFi and easily automated using the MQTT communication protocol. The programming of the microcontroller is performed on the Arduino IDE. The WiFi settings and the calibration value can be easily modified, stored and exported in the form of a JSON file to create a user friendly, plug and play and easily scalable device. Additional sensors or actuators can be added, allowing the system to adapt to various usages. Finally, in addition to its low manufacturing cost and its capability to fit a large variety of tasks involving liquid handling, our system has been specifically designed for research environments where adaptability and repeatability of experiments is essential.

Validation of molecular biomarkers for preoperative diagnostics of human papillary thyroid carcinoma in fine needle aspirates.

BACKGROUND: Despite substantial efforts, reliable preoperative diagnostic for human thyroid malignancies in case of cytologically indeterminate nodules is still missing, resulting in high number of unnecessary thyroidectomies. In an attempt to increase precision of existing preoperative diagnostics, we aimed at validating the panel of molecular biomarkers predictive for papillary thyroid carcinoma (PTC) in preoperative fine needle aspirate (FNA) samples. METHODS: In this prospective study conducted in preoperative thyroid FNA from 44 thyroid nodules, expression levels of 11 molecular biomarkers previously validated on the postoperative samples of PTCs were measured by Cell-to-CT and QuantiGene Plex methods and correlated with final diagnosis. RESULTS: The QuantiGene Plex resulted in reliable gene expression measurements for FNA and core-needle biopsy (CNB) samples, however this method was less sensitive than pre-amplification based Cell-to-CT. Measurements conducted on the same samples by the two methods significantly correlated for most of the genes. Expression levels of TIMP1, c-MET and ARNTL were upregulated in PTC nodules as compared to benign counterparts, supporting previous post-operative studies. Strong correlation was observed between these biomarker alterations in the same samples. Within the sub-group of 15 indeterminate nodules (Bethesda II-V), TIMP1 had 100% specificity and 83% sensitivity for PTC cases. CONCLUSIONS: Assessment of TIMP1, c-MET and core-clock gene ARNTL expression levels by QuantiGene Plex assay in FNA samples holds promise as an ancillary method to the cytological preoperative diagnostics.

Cellular circadian period length inversely correlates with HbA1c levels in individuals with type 2 diabetes.

AIMS/HYPOTHESIS: The circadian system plays an essential role in regulating the timing of human metabolism. Indeed, circadian misalignment is strongly associated with high rates of metabolic disorders. The properties of the circadian oscillator can be measured in cells cultured in vitro and these cellular rhythms are highly informative of the physiological circadian rhythm in vivo. We aimed to discover whether molecular properties of the circadian oscillator are altered as a result of type 2 diabetes. METHODS: We assessed molecular clock properties in dermal fibroblasts established from skin biopsies taken from nine obese and eight non-obese individuals with type 2 diabetes and 11 non-diabetic control individuals. Following in vitro synchronisation, primary fibroblast cultures were subjected to continuous assessment of circadian bioluminescence profiles based on lentiviral luciferase reporters. RESULTS: We observed a significant inverse correlation (ρ = -0.592; p < 0.05) between HbA1c values and circadian period length within cells from the type 2 diabetes group. RNA sequencing analysis conducted on samples from this group revealed that ICAM1, encoding the endothelial adhesion protein, was differentially expressed in fibroblasts from individuals with poorly controlled vs well-controlled type 2 diabetes and its levels correlated with cellular period length. Consistent with this circadian link, the ICAM1 gene also displayed rhythmic binding of the circadian locomotor output cycles kaput (CLOCK) protein that correlated with gene expression. CONCLUSIONS/INTERPRETATION: We provide for the first time a potential molecular link between glycaemic control in individuals with type 2 diabetes and circadian clock machinery. This paves the way for further mechanistic understanding of circadian oscillator changes upon type 2 diabetes development in humans. DATA AVAILABILITY: RNA sequencing data and clinical phenotypic data have been deposited at the European Genome-phenome Archive (EGA), which is hosted by the European Bioinformatics Institute (EBI) and the Centre for Genomic Regulation (CRG), ega-box-1210, under accession no. EGAS00001003622.

Newly Defined ATP-Binding Cassette Subfamily B Member 5 Positive Dermal Mesenchymal Stem Cells Promote Healing of Chronic Iron-Overload Wounds via Secretion of Interleukin-1 Receptor Antagonist.

In this study, we report the beneficial effects of a newly identified dermal cell subpopulation expressing the ATP-binding cassette subfamily B member 5 (ABCB5) for the therapy of nonhealing wounds. Local administration of dermal ABCB5+ -derived mesenchymal stem cells (MSCs) attenuated macrophage-dominated inflammation and thereby accelerated healing of full-thickness excisional wounds in the iron-overload mouse model mimicking the nonhealing state of human venous leg ulcers. The observed beneficial effects were due to interleukin-1 receptor antagonist (IL-1RA) secreted by ABCB5+ -derived MSCs, which dampened inflammation and shifted the prevalence of unrestrained proinflammatory M1 macrophages toward repair promoting anti-inflammatory M2 macrophages at the wound site. The beneficial anti-inflammatory effect of IL-1RA released from ABCB5+ -derived MSCs on human wound macrophages was conserved in humanized NOD-scid IL2rγ null mice. In conclusion, human dermal ABCB5+ cells represent a novel, easily accessible, and marker-enriched source of MSCs, which holds substantial promise to successfully treat chronic nonhealing wounds in humans. Stem Cells 2019;37:1057-1074.

Correction: Using the Dirichlet process to form clusters of people's concerns in the context of future party identification.

[This corrects the article DOI: 10.1371/journal.pone.0212944.].